Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study

The issue of information sharing and exchanging is one of the most important issues in the areas of artificial intelligence and knowledge-based systems (KBSs), or even in the broader areas of computer and information technology. This paper deals with a special case of this issue by carrying out a case study of information sharing between two well-known heterogeneous uncertain reasoning models: the certainty factor model and the subjective Bayesian method. More precisely, this paper discovers a family of exactly isomorphic transformations between these two uncertain reasoning models. More interestingly, among isomorphic transformation functions in this family, different ones can handle different degrees to which a domain expert is positive or negative when performing such a transformation task. The direct motivation of the investigation lies in a realistic consideration. In the past, expert systems exploited mainly these two models to deal with uncertainties. In other words, a lot of stand-alone expert systems which use the two uncertain reasoning models are available. If there is a reasonable transformation mechanism between these two uncertain reasoning models, we can use the Internet to couple these pre-existing expert systems together so that the integrated systems are able to exchange and share useful information with each other, thereby improving their performance through cooperation. Also, the issue of transformation between heterogeneous uncertain reasoning models is significant in the research area of multi-agent systems because different agents in a multi-agent system could employ different expert systems with heterogeneous uncertain reasonings for their action selections and the information sharing and exchanging is unavoidable between different agents. In addition, we make clear the relationship between the certainty factor model and probability theory.

Justice, gender and employee cognitive outcomes

This study used the four factor model of organizational justice to investigate gender differences in the employee outcome cognitive variables of job satisfaction,commitment and turnover intentions. Survey respondents were 301 male and 147 female currently working employees in a variety of occupations. Structural equation modeling was used for the analyses. There were significant relationships from distributive justice to job satisfaction and commitment for both men and women. Informational justice significantly predicted job satisfaction. For women, informational justice predicted commitment and turnover intentions. Procedural justice predicted turnover intentions and interpersonal justice predicted commitment for men. Gender differences were found for procedural, interpersonal and informational justices. Men and women gave differing responses to justice perceptions, implying consideration of a range of views when allocation decisions are made and communicated. For both genders, distributive and informational justices play a central role in predicting employee outcomes, although the other justice types also have an effect for males. Justice had a diffuse effect for males, but not females.

The factorial validity of emotional intelligence : an unresolved issue

An unresolved but pertinent issue in the field of emotional intelligence (EI) is factorial validity. Numerous studies have investigated this issue (Gignac, 2005; Mayer, Salovey, Caruso, & Sitarenios, 2003; Petrides & Furnham, 2000; Saklofske, Austin, & Minski, 2003), but most are based on correlations among subscale scores from relevant measures, making the implicit assumption that subscale scores are unidimensional, rather than questioning the structure of subscales themselves. Accordingly, the present study adopts the Anderson and Gerbing (1988) two-step strategy of first considering the structure within subscales before examining the relationship between subscales. An evaluation was undertaken using the Emotional Intelligence Scale (EIS, Schutte et al., 1998), the Work Profile Questionnaire – Emotional Intelligence Version (WQPei, Cameron, 1999) and the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT V.2., Mayer, Salovey, & Caruso, 1999b). Results were characterised by instability, heterogeneity and inconsistency. Specifically, the EIS was not found to form the homogenous structure postulated by authors. Similarly, support was not found for the seven factor model of the WPQei. Large discrepancies exist between the one, two and four factor models described by Mayer et al. (2003) for the MSCEIT V.2. and the 21 components revealed at the primary level in the current analyses. Additionally, reliability statistics for the MSCEIT V.2. were less than optimal. Questions remain regarding the clarity, reliability and validity of the instruments examined.

A new dimension of organizational justice : procedural voice

Dimensionality of the Colquitt justice measures was investigated across a wide range of service occupations. Structural equation modeling of data from 410 survey respondents found support for the 4-factor model of justice (procedural, distributive, interpersonal, and informational), although significant improvement of model fit was obtained by including a new latent variable, “procedural voice,” which taps employees’ desire to express their views and feelings and influence results. The model was confirmed in a second sample (N = 505) in the same organization six months later.

Productivity measurement of the construction industry in Australia

This research adopts the Malmquist total factor productivity model with Lovell's decomposition and renovated partial factor model to evaluate changes of productivity levels in Australia's construction industry. Research results find that the average annual productivity levels for Australian states are slowly growing, except for Queensland's total factor and capital productivities.

Cultural experience tourist motives dimensionality : a cross-cultural study

This empirical research of tourists’ cultural experiences aims to advance theory by developing a measurement model of tourists’ motives towards attending cultural experiences for samples of Western and Asian tourists visiting Melbourne, Australia. Drawing upon Iso-Ahola’s (1989) seeking/avoiding dichotomy theory for tourist motivation dimensions, the hypothesized dimensions primarily included escape and seeking-related dimensions, and some hedonic dimensions because of their relevance to aesthetic products (Hirschman & Holbrook, 1982; Holbrook & Hirschman, 1982), which are the context for this study. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to crossvalidate the underlying dimensionality structure of cultural experience motives. A four-factor model was extracted from the EFA consistent with some theoretical formulations and was retained in the CFA. Specific cultural language group differences for the motive dimensions were also hypothesized between Western and Asian tourist samples, and within the Chinese- and Japanese-speaking Asian tourist samples, but not within the different cultural groups of English-speaking Western tourists. These cross-cultural hypotheses were tested for the motive dimension measurement model using invariance testing in CFA. The findings for the motive dimensions differing by cultural group were not as expected. Significant cultural differences between Western and Asian tourists were not found, but a new finding of this study was significant differences between English-speaking tourists in their motives for attending cultural experiences. Marketing implications of these findings are also presented.

Latent variable models of need for uniqueness

The theory of uniqueness has been invoked to explain attitudinal and behavioral nonconformity with respect to peer-group, social-cultural, and statistical norms, as well as the development of a distinctive view of self via seeking novelty goods, adopting new products, acquiring scarce commodities, and amassing material possessions. Present research endeavors in psychology and consumer behavior are inhibited by uncertainty regarding the psychometric properties of the Need for Uniqueness Scale, the primary instrument for measuring individual differences in uniqueness motivation. In an important step toward facilitating research on uniqueness motivation, we used confirmatory factor analysis to evaluate three a priori latent variable models of responses to the Need for Uniqueness Scale. Among the a priori models, an oblique three-factor model best accounted for commonality among items. Exploratory factor analysis followed by estimation of unrestricted three- and four-factor models revealed that a model with a complex pattern of loadings on four modestly correlated factors may best explain the latent structure of the Need for Uniqueness Scale. Additional analyses evaluated the associations among the three a priori factors and an array of individual differences. Results of those analyses indicated the need to distinguish among facets of the uniqueness motive in behavioral research.

A slice sampler for restricted hierarchical beta process with applications to shared subspace learning

Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a hierarchical factor model allows factors to be shared across different sources. We derive a slice sampler for this model, enabling tractable inference even when the likelihood and the prior over parameters are non-conjugate. This allows the application of the model in much wider contexts without restrictions. We present two different data generative models – a linear Gaussian-Gaussian model for real valued data and a linear Poisson-gamma model for count data. Encouraging transfer learning results are shown for two real world applications – text modeling and content based image retrieval.

Practically and productively analysing Course Experience Questionnaire student comment data

Australia national survey of graduates from 1993 onward. In addition to quantitative items, the CEQ also includes an invitation to respondents to write open-ended comments on the best aspects (BA) of their university course experience and those most needing improvement (NI). These responses provide a rich source additional information that can help in understanding what students had in mind when agreeing or disagreeing with the CEQ response items. Based on more than 160,000 comments from students graduating from 14 Australian universities over the period 2001-2004, Scott (2006) developed a five domain model (Outcomes, Staff, Course design, Assessment and Support) for the classification of CEQ comments, as well as a software package (CEQuery) to automate the analysis of CEQ BA and NI comment data. While computer automated comment analysis is convenient, there are a number of known limitations to this approach, and where the number of student comments is not large, manual coding/classification is a viable, and arguably superior, approach.

Development and validation of the influenza intensity and impact questionnaire (FluiiQ™)

Objective
Clinical trials of new agents to reduce the severity and impact of influenza require accurate assessment of the effect of influenza infection. Because there are limited high-quality adult influenza Patient Reported Outcomes (PRO) measures, the aim was to develop and validate a simple but comprehensive questionnaire for epidemiological research and clinical trials.

Methods
Construct and item generation was guided by the literature, concept mapping, focus groups, and interviews with individuals with laboratory-confirmed influenza and expert physicians. Items were administered to 311 people with influenza-like illness (ILI) across 25 US sites. Analyses included classic psychometrics, structural equation modeling (SEM), and Rasch analyses.

Results
Concept mapping generated 149 concepts covering the influenza experience and clustered into symptoms and impact on daily activities, emotions, and others. Items were drafted using simplicity and brevity criteria. Eleven symptoms from the literature underwent review by physicians and patients, and two were removed and one added. The symptoms domain factored into systemic and respiratory symptoms, whereas the impact domains were unidimensional. All domains displayed good internal consistency (Cronbach α ≥ 0.8) except the three-item respiratory domain (α = 0.48). A five-factor SEM indicated excellent fit where systemic, respiratory, and daily activities domains differentiated patients with ILI or confirmed influenza. All scales were responsive over time.

Conclusions
Patient and clinician consultations resulted in an influenza PRO measure with high validity and good overall evidence of reliability and responsiveness. The Influenza Intensity and Impact Questionnaire (FluiiQ™) will improve the evaluation of existing and future agents designed to prevent or control influenza infection by increasing the breadth and depth of measurement in this field.

Gambling motives: application of the reasons for gambling questionnaire in an Australian population survey

The Reasons for Gambling Questionnaire (RGQ) consist of 15 items forming five factors: enhancement, social, money, recreation and coping. The RGQ was developed for use in the 2010 British Gambling Prevalence Survey (BGPS) and has now been employed in the second Social and Economic Impact Study (SEIS) of Gambling in Tasmania study conducted in 2011 in Australia. Given differences between Britain and Australia in terms of socio-demographic profiles, gambling cultures and attitudes, gambling access and availability, gambling regulation, and rates and patterns of gambling participation, the aims of this study were to analyse the RGQ data from the SEIS to: (1) determine the most commonly endorsed gambling motives in an Australian jurisdiction, (2) explore the factor structure of the RGQ in an Australian sample, and (3) explore how motives for gambling vary among different Australian population sub-groups. A representative sample of the Tasmanian population who had gambled in the previous 12 months (n = 2,796) were administered the RGQ via computer-assisted telephone interviewing. The five most commonly endorsed reasons for gambling were for fun (62 %), followed by the chance of winning big money (52 %), it being something to do with friends and family (48 %), to be sociable (40 %), and excitement (38 %). A principal component analysis revealed a five-factor structure that is slightly different from that derived in the BGPS: money, regulate internal state, positive feelings, social, and challenge reasons. Finally, gambling motives varied according to socio-demographic factors, number of gambling activities, problem gambling severity, and participation on different gambling activities. Although some of these findings are consistent with those from the BGPS, there are also some slight differences, suggesting that there may be regional-specific variations in gambling motives.

The construct validity of the work-related flow inventory in a sample of Australian workers

The purpose of this study was to examine the construct validity of the WOrk-reLated Flow inventory (WOLF; Bakker, 2008). This instrument was administered to 711 men and women who were working in Queensland, Australia. The results from the confirmatory factor analysis showed that the WOLF has moderately acceptable construct validity, with the three-factor model being a borderline fit to the data. Tests of the convergent validity of the WOLF yielded satisfactory results. However, the analysis of the discriminant validity of the WOLF showed that the instrument poorly discriminated between work enjoyment and intrinsic work motivation. Follow-up exploratory factor analysis, using recommended procedures for determining the number of factors to extract, revealed a two-factor solution, with the work enjoyment and intrinsic work motivation items loading on the same factor. Drawing on literature on psychological flow and motivation, as well as the findings of the present study, questions are raised over the adequacy of the conceptual basis of the three-factor model of work-related flow, the discriminant validity of the WOLF subscales, and the appropriateness of the wording of several of this measure's items. Using alternative methods and measures to investigate flow in work settings is recommended.

On the determination of the number of factors using information criteria with data-driven penalty

As is well known, when using an information criterion to select the number of common factors in factor models the appropriate penalty is generally indetermine in the sense that it can be scaled by an arbitrary constant, c say, without affecting consistency. In an influential paper, Hallin and Liška (J Am Stat Assoc102:603–617, 2007) proposes a data-driven procedure for selecting the appropriate value of c. However, by removing one source of indeterminacy, the new procedure simultaneously creates several new ones, which make for rather complicated implementation, a problem that has been largely overlooked in the literature. By providing an extensive analysis using both simulated and real data, the current paper fills this gap.

Estimating cointegrated panels with common factors and the forward rate unbiasedness hypothesis

This article proposes a bias-adjusted estimator for use in cointegrated panel regressions when the errors are cross-sectionally correlated through an unknown common factor structure. The asymptotic distribution of the new estimator is derived and is examined in small samples using Monte Carlo simulations. For the estimation of the number of factors, several information-based criteria are considered. The simulation results suggest that the new estimator performs well in comparison to existing ones. In our empirical application, we provide new evidence suggesting that the forward rate unbiasedness hypothesis cannot be rejected. © The Author 2007.

The local power of the CADF and CIPS panel unit root tests

Very little is known about the local power of second generation panel unit root tests that are robust to cross-section dependence. This article derives the local asymptotic power functions of the cross-section argumented Dickey–Fuller Cross-section Augmented Dickey-Fuller (CADF) and CIPS tests of Pesaran (2007), which are among the most popular tests around.